Journal ArticleDOI
Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems
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TLDR
The results of the proposed algorithm on the test functions show that this algorithm benefits from high convergence and coverage, and its applicability is solving challenging real-world problems as well.Abstract:
This paper proposes a multi-objective version of the recently proposed Ant Lion Optimizer (ALO) called Multi-Objective Ant Lion Optimizer (MOALO). A repository is first employed to store non-dominated Pareto optimal solutions obtained so far. Solutions are then chosen from this repository using a roulette wheel mechanism based on the coverage of solutions as antlions to guide ants towards promising regions of multi-objective search spaces. To prove the effectiveness of the algorithm proposed, a set of standard unconstrained and constrained test functions is employed. Also, the algorithm is applied to a variety of multi-objective engineering design problems: cantilever beam design, brushless dc wheel motor design, disk brake design, 4-bar truss design, safety isolating transformer design, speed reduced design, and welded beam deign. The results are verified by comparing MOALO against NSGA-II and MOPSO. The results of the proposed algorithm on the test functions show that this algorithm benefits from high convergence and coverage. The results of the algorithm on the engineering design problems demonstrate its applicability is solving challenging real-world problems as well.read more
Citations
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Journal ArticleDOI
Grasshopper optimization algorithm for multi-objective optimization problems
TL;DR: A mathematical model is first employed to model the interaction of individuals in the swam including attraction force, repulsion force, and comfort zone and then a mechanism is proposed to use the model in approximating the global optimum in a single-objective search space.
Journal ArticleDOI
Optimal distributed generation planning in active distribution networks considering integration of energy storage
TL;DR: In this article, a two-stage optimization method is proposed for optimal distributed generation (DG) planning considering the integration of energy storage in the PG&E 69-bus distribution system.
Journal ArticleDOI
A novel hybrid system based on a new proposed algorithm-Multi-Objective Whale Optimization Algorithm for wind speed forecasting
TL;DR: The results indicate that the proposed MOWOA performs better than the two recently developed MOALO and MODA algorithms, and thatThe proposed hybrid model outperforms all sixteen models used for comparison, which demonstrates its superior ability to generate forecasts in terms of forecasting accuracy and stability.
Journal ArticleDOI
A novel hybrid forecasting system of wind speed based on a newly developed multi-objective sine cosine algorithm
TL;DR: A hybrid forecasting system based on a newly developed algorithm—referred to as the multi-objective sine cosine algorithm (MOSCA)—is developed, which includes four modules, specifically, data preprocessing, optimization, forecasting, and evaluation module, and it is concluded that the proposed approach can be an efficient and effective technique for wind speed forecasting.
Journal ArticleDOI
Golden eagle optimizer: A nature-inspired metaheuristic algorithm
TL;DR: A nature-inspired swarm-based metaheuristic for solving global optimization problems called Golden Eagle Optimizer (GEO), which shows GEO’s superiority, which indicates that it can find the global optimum and avoid local optima effectively.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Book
Multi-Objective Optimization Using Evolutionary Algorithms
Kalyanmoy Deb,Deb Kalyanmoy +1 more
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Journal ArticleDOI
No free lunch theorems for optimization
TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
Journal ArticleDOI
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Eckart Zitzler,Lothar Thiele +1 more
TL;DR: The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface.